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# From describing to doing: How MCP makes AI-driven Ansible automation reliable

**[Red Hat Developer](https://daily.dev/sources/rhdev)** · 10 min read · 0 upvotes · 0 comments

## Summary

Red Hat introduces the Ansible development tools MCP server, which connects AI assistants like GitHub Copilot, Claude Code, Gemini CLI, Cursor, and Windsurf directly to Ansible CLI tools (ansible-lint, ansible-creator, ansible-navigator) through the Model Context Protocol. Instead of an AI merely describing how to run a command, it can execute linting, scaffolding, environment setup, and playbook runs deterministically, using the developer's actual local environment context to avoid hallucinated module names or missing dependencies. The server ships bundled in the Ansible VS Code extension, is available as a container image or via npx, and is currently a Technology Preview. It pairs with an Ansible Automation Platform MCP server (GA in Ansible Automation Platform 2.7) for job management and inventory queries at the operational layer, with RBAC-scoped tokens recommended for non-production use.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://developers.redhat.com/articles/2026/08/19/red-hat-ansible-development-tools-mcp-server>

## Questions this post answers

### How do I connect Claude Code to the Ansible development tools MCP server?

Run 'claude mcp add ansible -- npx -y @ansible/ansible-mcp-server --stdio' from the terminal. This registers the Ansible development tools MCP server with Claude Code, giving it access to tools like ansible-lint, ansible-creator, and ansible-navigator through the Model Context Protocol rather than generic shell command suggestions.

_Developers wiring AI assistants into Ansible workflows can track tooling changes like this via daily.dev._

### What does the Ansible development tools MCP server actually let an AI assistant do differently compared to a normal chat response?

Instead of just explaining how to run ansible-lint or ansible-creator, the AI directly executes them through defined MCP tool calls with full parameter schemas, then applies fixes and iterates until the code is clean. It covers code quality (lint plus auto-fix), project scaffolding, playbook execution via ansible-navigator, environment management, and execution environment container builds.

_Teams weighing AI-assisted automation tooling can follow developments like the Ansible MCP server on daily.dev._

### When does the Ansible Automation Platform gateway expose MCP endpoints for job management and inventory queries?

MCP endpoint support in the Ansible Automation Platform gateway is available starting with Ansible Automation Platform 2.5 and becomes generally available in Ansible Automation Platform 2.7, enabling structured MCP calls for job management, inventory queries, and system monitoring under role-based access control.

_Platform engineers tracking Ansible Automation Platform capabilities can follow release details on daily.dev._

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---

Tags: [#devops](https://daily.dev/tags/devops), [#ai-coding](https://daily.dev/tags/ai-coding), [#mcp](https://daily.dev/tags/mcp), [#red-hat](https://daily.dev/tags/red-hat), [#ansible](https://daily.dev/tags/ansible)

[View this post on daily.dev](https://daily.dev/posts/from-describing-to-doing-how-mcp-makes-ai-driven-ansible-automation-reliable-b1gvvlzp4)

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